SYBB 464

Artificial Intelligence for Biomedical Research

Course Overview

Artificial Intelligence for Biomedical Research (SYBB 464) is an active learning course designed to equip graduate students with a comprehensive understanding of Artificial Intelligence (AI) methodologies and their direct applications in biomedical research.

Going beyond theory, this course focuses on building real-world analysis skills. Students will transition from understanding AI concepts to critically evaluating bioinformatics approaches and implementing them to solve complex biological problems. Whether you are interested in genomics, drug discovery, or medical imaging, this course provides the foundational and practical skills necessary to handle high-dimensional biological data.

Instructor Information

  • Instructor: Gürkan Bebek, Ph.D., M.S.
  • Office: CWRU BRB 921
  • Office Hours: Tuesdays, 12:00 pm – 1:00 pm
  • Email: gurkan.bebek@case.edu

Prerequisites

{SYBB 402 and SYBB 411} OR {SYBB 412} OR Instructor Consent. Note: This course is designed for graduate students and is particularly relevant for those with an interest in bioinformatics and systems biology.

What You’ll Learn

In SYBB 464, students will master the AI/ML tools integral to contemporary biomedical investigations. Key topics include:

  • Machine Learning Fundamentals: Master supervised and unsupervised learning techniques specifically applied to systems biology and bioinformatics problems.
  • Deep Learning & Medical Imaging: Explore Convolutional Neural Networks (CNNs) for analyzing radiology, pathology, and 3D imaging data.
  • Natural Language Processing (NLP): Learn to extract critical information from medical literature and clinical records using text mining and Named Entity Recognition (NER).
  • AI for Drug Discovery: Use AI to identify drug targets, predict toxicity, and drive drug repurposing efforts.
  • Precision Medicine & Genomics: Apply predictive analytics to patient care, tailoring treatments based on genomic data and individual patient characteristics.
  • Robotics & Surgery: Understand the role of AI in surgical decision support and autonomous robotic surgery.
  • Ethics & Explainable AI: Design solutions that consider data privacy, patient impact, and the importance of interpretability in medical AI models.

Course Format

This course utilizes a Problem-Based Active Learning strategy. You won’t just listen to lectures; you will do the work.

  • Hands-On Labs: “The only way to learn bioinformatics is to do it!” Weekly labs involve coding and data analysis using real-world tools.
  • Student-Led Discussions: Engage deeply with the material by leading and participating in discussions on cutting-edge peer-reviewed publications.
  • Capstone Project: The semester culminates in a group project where you will perform a reproducible bioinformatics analysis on a large dataset using ML/AI, producing a written report and presentation.

Why Do You Want This Course?

1. Career Readiness in a Booming Field AI and Machine Learning are transforming biology and medicine. Employers in pharma, biotech, and academia are actively seeking candidates who can bridge the gap between biological inquiry and computational modeling. This course gives you that exact skillset.

2. Build a Portfolio You won’t just take exams; you will build a Semester Project. This allows you to leave the course with a tangible, reproducible analysis of a large dataset—something you can show to future employers or PI’s to demonstrate your competency.

3. Practical, Not Just Theoretical Many courses discuss what AI is; this course teaches you how to use it. Through weekly hands-on labs, you will gain confidence using the actual tools and code required for modern systems biology.

4. Networking and Expert Insight Learn directly from an experienced instructor and engage with peers in a seminar-style environment that mimics professional scientific collaboration.

For more information, please request the full syllabus via email (available to CWRU students only).

Course Logistics

  • Time: Tue/Thu 1:00 PM – 2:15 PM
  • Prerequisites: SYBB 402 & 411 OR SYBB 412 (or consent)
  • Format: In-Person
  • Tech: Laptop with Admin privileges and >8GB RAM
  • Textbook: None required (Readings on Canvas)